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Đorđe Jakovljević

3 papers indexed

zenodoConference paper2026-05-20

Differentiating Suspected and Confirmed Heart Failure Using Machine Learning and Refined Vocal Features

Lazar Dašić, Ognjen Pavić, Tijana Geroski, Anđela Blagojević, Andrej Preveden, Aleksandra Milovančev, et al.

Voice characteristics are an emerging, non-invasive biomarker for heart failure. This study develops a machine learning pipeline to differentiate patients with suspected heart failure from those with a confirmed diagnosis using vocal features alone, drawing on 240 patients (50 su…

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zenodoConference paper2026-05-20

Differentiating Suspected and Confirmed Heart Failure Using Machine Learning and Refined Vocal Features

Lazar Dašić, Ognjen Pavić, Tijana Geroski, Anđela Blagojević, Andrej Preveden, Aleksandra Milovančev, et al.

Voice characteristics are an emerging, non-invasive biomarker for heart failure. This study develops a machine learning pipeline to differentiate patients with suspected heart failure from those with a confirmed diagnosis using vocal features alone, drawing on 240 patients (50 su…

View free PDFSource page
zenodoConference paper2026-05-20

Echocardiography View Classification as an Important Step to Heart Failure Diagnosis: A Case Study of the EchoJEPA Foundation Model

Ognjen Pavić, Lazar Dašić, Tijana Geroski, Anđela Blagojević, Andrej Preveden, Aleksandra Milovančev, et al.

Accurate classification of echocardiographic views (e.g. apical 2- and 4-chamber, parasternal long-axis) is an important prerequisite for reliable ejection-fraction assessment and heart failure diagnosis, but manual classification is time-consuming. This study evaluates the EchoJ…

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